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Record W4400149484 · doi:10.14740/jem942

Pharmacological Treatment of Diabetes Mellitus: An Overview of New Sodium-Glucose Cotransporter 2 Inhibitors for the Treatment of Diabetes Mellitus

2024· article· en· W4400149484 on OpenAlexvenueno aff
Mateusz Nieczyporuk, Paweł Tyrna, Tomasz Cader, Aleksandra Sikora, Szymon Staneta

Bibliographic record

VenueJournal of Endocrinology and Metabolism · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiabetes mellitusRenal glucose reabsorptionType 2 Diabetes MellitusInternal medicineBlood pressureEndocrinologyType 2 diabetesInsulinOverweightObesity

Abstract

fetched live from OpenAlex

Diabetes mellitus is a metabolic disease characterized by chronic hyperglycemia, which leads to irreversible damage to the vascular endothelium and causes many complications. Type 2 diabetes accounts for the vast majority of cases and is characterized by a deficit of insulin action on tissues. In recent years, several new oral drugs have emerged to treat the disease, including sodium-glucose cotransporter 2 (SGLT2) inhibitors (flozins) that prevent glucose reabsorption in the kidneys. In this review, we analyzed seven different SGLT2 inhibitors, including several novel ones, based on 38 selected papers. Flozins display high efficacy in reducing hemoglobin A1c (HbA1c), body weight, and systolic blood pressure. Therefore, flozins should be considered one of first-line treatment options in type 2 diabetes not only for patients with heart failure or kidney disease, but also for overweight and hypertensive patients. J Endocrinol Metab. 2024;14(3):89-102 doi: https://doi.org/10.14740/jem942

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.330
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

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